Two-way radio communication of voice signals is an essential capability for modern society. Organizations involved in police work, public safety, and transportation are major users of voice communication, to say nothing of military users. With increasing demands being placed upon available radio frequency spectrum, much research has been done on maximizing spectrum efficiency.
One way to increase spectrum efficiency is to compress speech signals prior to transmission. This compression operation, as is well-known in the art, reduces bandwidth requirements for the transmission of voice signals and permits the assignment of more RF (radio frequency) communication channels within a given range of frequencies. Similarly, speech compression algorithms may also be applied to digital speech storage.
With the increasing emphasis on digital communication, compression schemes peculiar to digital systems have received much attention. Compression schemes dedicated to digitized speech are commonly referred to as voice coders. U.S. Pat. No. 4,933,957 to Bottau et al. describes a low bit rate voice coding method and system exemplary of those commonly known in the art.
Linear predictive coding, or LPC, is an example of a popular voice coding technique. In LPC, an attempt is made to approximate human speech by deriving appropriate models for both the human vocal tract and for excitations applied to the vocal tract. Since speech is a very repetitive type of signal, the amount of information required to allow a decoder to accurately reproduce a speech waveform can be much reduced. Depending upon the nature of the speech being transmitted, some bits may be more perceptually significant to the reconstructed speech than others.
As with any type of digital signal, decisions must be made at the decoder regarding whether a logic "1" level or a logic "0" level was originally transmitted. Error control coding, a concept well-understood in the art, is often employed to increase the likelihood that the decoder will make correct decisions. Of course, it is self-defeating to compress digital speech for transmission only to add a large number of error control bits. A compromise must be reached in order to maximize the effectiveness of a given speech compression algorithm while trying to ensure speech quality by guaranteeing error-free reception of critical bits. Of course, critical bits can be identified for a variety of data transmission scenarios that do not involve speech coding applications.
Accordingly, a need arises for a method for error protecting critical bits for transmission, where the specific bits requiring protection may be dependent upon a subset of input bits such as, for example, the set of bits identifying the type of speech waveform being coded. The specific bits requiring protection could also be determined by expected communication channel conditions.